OOF-AII-826493
Facebook translates 'good morning' into 'attack them', leading to arrest
Facebook's automatic language translation software incorrectly translated an Arabic post saying "Good morning" into Hebrew saying "hurt them," leading to the arrest of a Palestinian man in Beitar Illit, Israel.
- Event date
- 2017-10-17
- Country
- Palestine
- Severity
- Low
- Evidence state
- Single-source
Assessment status
Generated from available public incident evidence using OOF® governance methodology. It is not an official investigation, legal determination, regulatory finding, certification, or OOF® Approved Assessment.
View source record from AI Incident Database (Responsible AI Collaborative)
Assessment confidence dimensions
- Source corroboration
- Single-source
- Extraction completeness
- High
- Methodological assignment confidence
- Moderate
Measures source-group corroboration only; it does not establish factual truth.
Measures populated source fields after deterministic normalization; it does not measure correctness.
Measures automated assignment support; substantive correctness requires authorized human review.
Known facts from the incident record
- The incident record identifies the event date as 2017-10-17.
- The incident record identifies the location as Palestine.
Reported claims
- Facebook's automatic language translation software incorrectly translated an Arabic post saying "Good morning" into Hebrew saying "hurt them," leading to the arrest of a Palestinian man in Beitar Illit, Israel.
Material unknowns
- Independent corroboration is not established in the available incident record.
Primary governance problem
The incident appears to expose a governance problem involving into, communication, information, distributional. Available reporting supports preliminary methodological interpretation, not a finding of fault or non-compliance.
Architecture intelligence
PGA™ — Prediction Governance Architecture
Primary architecture
The reported into, communication, information concern falls within the governed questions represented by PGA™ — Prediction Governance Architecture.
Governance focus: How must a prediction and its complete history remain identifiable, reconstructable, versioned, and historically continuous across formation, revision, supersession, outcome, performance assessment, retirement, and lifecycle re-entry?
Canonical methodology (ParentStandard):
Preliminary governance questions
- How must a prediction and its complete history remain identifiable, reconstructable, versioned, and historically continuous across formation, revision, supersession, outcome, performance assessment, retirement, and lifecycle re-entry?
- What operational authority and controls applied to Facebook at the relevant time?
- What evidence would establish how yes produced or enabled the reported outcome?
- What additional independent evidence is required to resolve the material evidence gaps?
Evidence gaps and limitations
- Only one independent source group is represented; corroboration is not established.